1. Field of the Invention
This invention relates to a radar signal processing unit and radar signal processing method of a radar for measuring the atmosphere.
2. Related Art
Information on the wind direction and the wind speed is one of the information required for weather forecasting. The most general method of measuring the wind direction and the wind speed is to install an anemoscope and an anemometer on the ground, in which case the wind only in the vicinity of the surface of the earth can be measured with the anemoscope and the anemometer on the ground. To make more precise weather forecasting, it is also necessary to know the wind direction and the wind speed in the sky; however, hitherto the wind in the sky has been able to be measured only by observation with a sonde, etc. The sonde observation has a disadvantage in that the time resolution of the observation is low (several hours or more) because only the data at the time at which the sonde is floated can be provided.
In contrast, in recent years, an art of measuring the wind direction and the wind speed in the sky by an atmospheric radar called wind profiler has been established. The wind profiler makes it possible to measure the wind direction and the wind speed in the sky every minute to every several minutes. It is expected that the wind information in the sky with such high time resolution will become useful for enhancing the accuracy of weather forecasting.
Here, the principle of measuring the atmosphere with the wind profiler will be discussed. The wind profiler is a kind of Doppler radar and generally has a configuration as shown in FIG. 20. In the figure, numeral 101 denotes an antenna, numeral 102 denotes a transmitter-receiver, numeral 103 denotes a radar signal processing unit, numeral 104 denotes a quality control processing unit, numeral 105 denotes a wind vector calculation unit, and numeral 106 denotes a display/record unit.
Next, the operation is as follows: A radio wave generated in the transmitter-receiver 102 is radiated through the antenna 101 into the air. The radio wave radiated into the air is reflected on a scattering volume produced because of the fluctuation of the refractive index of the atmosphere. The reflected radio wave is received at the antenna 101 and is input to the transmitter-receiver 102. If the scattering volume flows together with the wind in the sky, the received radio wave changes in frequency because of the Doppler effect. This frequency changes is detected as with a general Doppler radar, whereby the wind speed in the sky is detected. Specifically, the transmitter-receiver 102 amplifies, frequency-converts, and detects the received radio wave to generate a video signal and outputs the video signal to the radar signal processing unit 103, which then performs frequency analysis processing for the video signal, thereby calculating Doppler frequency, and further calculates the Doppler velocity from the Doppler frequency.
FIG. 21 is a block diagram to represent the internal configuration of the radar signal processing unit 103. In the figure, numeral 1 denotes a Fourier transform section, numeral 2 denotes a frequency domain power calculation section, numeral 4 denotes an incoherent integration section, and numeral 5 denotes a signal detection section. The Fourier transform section 1 transforms a received signal obtained for each distance from a time domain signal into a frequency domain signal. To do this, for example, Fast Fourier Transform (FFT) may be used or any other technique may be used. The frequency domain signal is input to the frequency domain power calculation section 2, which then calculates the electric power for each frequency component, thereby providing a power spectrum. The incoherent integration section 4 integrates the power spectra, thereby decreasing the fluctuations in the power spectrum. The signal detection section 5 detects the spectrum peak of atmospheric echo from the power spectrum provided by performing the incoherent integration and calculates the Doppler velocity, namely, the physical quantity of the atmosphere such as the radial wind speed from the frequency of the spectrum peak.
The quality control processing unit 104 inputs the Doppler velocity data output from the radar signal processing unit 103 and assumes the time and space continuity of the atmosphere, thereby determining that discontinuous data in the time axis and space axis directions is low-accuracy data and removing the data as missing data. Then, the quality control processing unit 104 outputs the remaining data as high-accuracy data.
The wind vector calculation unit 105 inputs the Doppler velocity data observed in different beam directions and combines the Doppler velocity data, thereby calculating a three-dimensional wind vector. FIGS. 22A and 22B schematically show the principle of calculating the wind vector. FIG. 22A shows typical beam directions when the wind speed in the sky is measured. Here, the beam is switched north, south, east and west in the zenith direction and about 10 degrees of zenith angle. FIG. 22B shows that the situation in FIG. 22A is cut on the vertical cross section parallel with an east-west direction. If a wind blows from the west to the east, the Doppler velocity in the approaching direction is observed if it is observed with the west beam and the Doppler velocity in the away direction is observed if it is observed with the east beam. The difference between the Doppler velocity observed with the west beam and the Doppler velocity observed with the east beam can be used to find the wind speed in the east-west direction. Likewise, if the north beam and the south beam are used, the wind speed in the south-north direction can be obtained. Further, the Doppler velocity in the zenith direction corresponds to the vertical component of the wind speed. Consequently, a three-dimensional wind vector can be provided.
The display/record unit 106 displays or records the wind vector data output from the wind vector calculation unit 105.
As a quality control processing system in a related art, a quadric surface approximation system proposed in an article about “Wind profiler” in a book called Sokkou Jihou 65.3, 1998 is available. FIG. 23 is a block diagram to show the configuration of a quality control processing unit to implement the quadric surface approximation system. In the figure, numeral 401 denotes an approximate surface definition range setting section, numeral 402 denotes an approximate quadric surface calculation section, numeral 403 denotes an approximate accuracy determination section, and number 404 denotes a data removal section.
Next, the operation of the quality control processing unit shown in FIG. 23 will be discussed. The approximate surface definition range setting section 401 sets the time range and the distance range for defining an approximate quadric surface when a quadric surface is fitted to measurement data. The approximate quadric surface calculation section 402 fits the quadric surface to input data in the time range and the distance range set by the approximate surface definition range setting section 401. To fit the quadric surface, for example, a least square method is used.
The approximate accuracy determination section 403 determines whether or not the accuracy of the approximate quadric surface calculated by the approximate quadric surface calculation section 402 is high. For example, in the document mentioned above, the difference between the measurement value at the grid point at each time and distance and the approximate quadric surface is calculated and if the maximum value of the difference is greater than a preset threshold value or if the square root of the root mean square of the differences in the approximate surface definition range is greater than a preset threshold value, the accuracy of the approximate quadric surface is determined low.
If the accuracy of the approximate quadric surface is low, the Doppler velocity data and the approximate quadric surface are input to the data removal section 404, which then removes the Doppler velocity data as missing data at the grid point where the difference between the approximate quadric surface and the Doppler velocity data is large. The Doppler velocity data subjected to the data removal processing in the data removal section 404 is input to the approximate quadric surface calculation section 402, which again fits the quadric surface to input data. Such process is repeated until the approximate accuracy determination section 403 determines that the accuracy of the approximate quadric surface is high.
If the approximate accuracy determination section 403 determines that the accuracy of the approximate quadric surface is high, it outputs the Doppler velocity data at this point in time as the data already undergoing the quality control processing. Then, the approximate surface definition range setting section 401 updates the definition range of the approximate surface to the next order or the next time and repeats the same process.
The quality control processing according to the quadric surface approximation system as described above operates well if the number of grid points where the data quality is degraded is small. For example, if one bird only exists in the sky above a radar, the Doppler velocity corresponding to the move speed of the bird is observed only at one point of the space-time coordinates and the Doppler velocity corresponding to the wind, namely, the radial wind speed is observed at other points. Therefore, the quality control processing unit previously described with reference to FIG. 23 can be used to remove only the bird echo.
However, if a large number of birds come flying consecutively in time sequence, the number of grid points where the data quality is degraded is increased. Then, in the space-time coordinates, migratory bird echo is detected more prominently than the atmospheric echo. In this case, it becomes difficult to remove an abnormal echo by the quality control processing unit in the related art as previously described with reference to FIG. 23. Such a situation frequently occurs when a season wherein migratory birds move all together comes.
Since the radar beam is thin, the time for the bird to pass through the beam is limited. Therefore, a bird echo is received intermittently in time sequence. In the time when the bird echo is broken, only the atmospheric echo can be received. However, since the radar cross section of bird is large as compared with that of the atmosphere, if integration processing of integrating data in the time direction is performed, only the bird echo with large radar cross section is prominent and the atmospheric echo is buried. Accordingly, bird echo appears continuously in time sequence in the data after undergoing signal processing.